The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Machine Learning Approach for Tracing Tumor Original Sites With Gene Expression Profiles
|
|---|---|
| Published in |
Frontiers in Bioengineering and Biotechnology, November 2020
|
| DOI | 10.3389/fbioe.2020.607126 |
| Pubmed ID | |
| Authors |
Xin Liang, Wen Zhu, Bo Liao, Bo Wang, Jialiang Yang, Xiaofei Mo, Ruixi Li |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 6% |
| Comoros | 1 | 6% |
| United States | 1 | 6% |
| United Kingdom | 1 | 6% |
| Unknown | 12 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 50% |
| Scientists | 5 | 31% |
| Practitioners (doctors, other healthcare professionals) | 2 | 13% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 25% |
| Other | 1 | 13% |
| Student > Postgraduate | 1 | 13% |
| Unknown | 4 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 1 | 13% |
| Agricultural and Biological Sciences | 1 | 13% |
| Medicine and Dentistry | 1 | 13% |
| Engineering | 1 | 13% |
| Unknown | 4 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 November 2020.
All research outputs
#4,715,487
of 23,342,232 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#691
of 6,980 outputs
Outputs of similar age
#127,439
of 509,020 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#50
of 300 outputs
Altmetric has tracked 23,342,232 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,980 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 509,020 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 300 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.